model-usage

model-usage is a skill for Claude Code, Codex from geezerrrr/motive. It costs 69 tokens per session (563 once invoked), scanned A, a copy of model-usage, MIT.

A command-line report for summarizing Codex or Claude usage costs by model from CodexBar’s local records.

In plain words
What is it for?
Use it to report the current most-used model or produce a breakdown of all models, using CodexBar output, a JSON file, or standard input.
Why use it?
It makes model-specific usage easier to inspect than reading raw cost data or manually comparing daily entries.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/geezerrrr/motive/model-usage
Any agent
npx skills add geezerrrr/motive --skill model-usage
Clone the repo
git clone --depth 1 https://github.com/geezerrrr/motive

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for model-usage

README.md
[![agentmods](https://agentmods.dev/badge/skills/geezerrrr/motive/model-usage.svg)](https://agentmods.dev/skills/geezerrrr/motive/model-usage)
Your own site
<a href="https://agentmods.dev/skills/geezerrrr/motive/model-usage"><img src="https://agentmods.dev/badge/skills/geezerrrr/motive/model-usage.svg" alt="Measured on agentmods" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 563 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00069 $0.00563
Opus 5 $0.00034 $0.00282
Sonnet 5 $0.00014 $0.00113
Haiku 4.5 $0.00007 $0.00056

Measured 4d ago against content hash b88045ef1c5c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

model-usage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/model_usage.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

94% identical to model-usage — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

Motive/Resources/Skills.bundle/model-usage/SKILL.md · 70 lines

What it actually says

Model usage

Overview

Get per-model usage cost from CodexBar's local cost logs. Supports "current model" (most recent daily entry) or "all models" summaries for Codex or Claude.

TODO: add Linux CLI support guidance once CodexBar CLI install path is documented for Linux.

Quick start

  1. Fetch cost JSON via CodexBar CLI or pass a JSON file.
  2. Use the bundled script to summarize by model.
python {baseDir}/scripts/model_usage.py --provider codex --mode current
python {baseDir}/scripts/model_usage.py --provider codex --mode all
python {baseDir}/scripts/model_usage.py --provider claude --mode all --format json --pretty

Current model logic

  • Uses the most recent daily row with modelBreakdowns.
  • Picks the model with the highest cost in that row.
  • Falls back to the last entry in modelsUsed when breakdowns are missing.
  • Override with --model <name> when you need a specific model.

Inputs

  • Default: runs codexbar cost --format json --provider <codex|claude>.
  • File or stdin:
codexbar cost --provider codex --format json > /tmp/cost.json
python {baseDir}/scripts/model_usage.py --input /tmp/cost.json --mode all
cat /tmp/cost.json | python {baseDir}/scripts/model_usage.py --input - --mode current

Output

  • Text (default) or JSON (--format json --pretty).
  • Values are cost-only per model; tokens are not split by model in CodexBar output.

References

  • Read references/codexbar-cli.md for CLI flags and cost JSON fields.
Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 70 lines · 69 tokens per session scan A b88045ef1c5c

Subscribe to this mod's changes

model-usage is a skill published in the GitHub repository geezerrrr/motive (117 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 563 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to model-usage, differing in 2 lines, and is treated as a copy.

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